To make the most of the data they hold, businesses need to think beyond the limits of what data can do for their current customers and start to understand how it can shape the whole ecosystem they operate in, says digital and innovation leader and Cognition-X Advisory Board member Hugo Pinto. 

He explained why at a recent event held by our Consumer and Organisational Digital Analytics Centre.

Tell us what made you decide to focus on data analytics?

I’d been working in Marketing and Digital technologies, mostly using data to understand users and to support our own decision-making.  That changed with my experience at Telefonica where my team that started out by advising businesses on consumer behaviour, but started to see the data we used as a tool that could solve fundamental problems, improve processes and shape strategy.

Afterwards I moved to IBM, which enabled me to codify this approach and apply it across a range of industries.  This variety means my learning journey will never end!

Businesses talk about being customer-centric, but you say they can use data to change the system they work in; what’s the advantage of that?

Some services are again in a reinvention stage, just like the railways disrupted the horse as a means of transportation. But if you don’t see beyond designing the perfect train, then you will not understand you could have a value proposition to the fuel, logistics and agriculture industries – or even the potential to create an entirely new category like mass public transport or mass leisure travel.

The mobile devices we all carry allow us to quantify physical world behaviour and context in immense detail and in almost real time.  We can use this information to understand what matters to consumers and individuals, why it matters and how you can create better outcomes for them.

We hear a lot about disruption, how easy is it to actually achieve?

Not that easy.  It’s one thing to have disruptive ideas and another thing to market them. A good example is a project I developed around using weather data to understand the triggers for my asthma.  I hacked my asthma inhaler with a click button, a SIM card and a cheap and really widely available computing board called an Arduino board so that it could capture data about when and where I had an asthma crisis – which might happen when I was out running.

We combined this data with publicly available weather data and used machine learning to predict when I’d have a crisis and would need to use my inhaler preventively to avoid it.   For an asthma sufferer predicting and preventing crises is a good outcome because it can take some days to recover from an attack. What’s more the solution is potentially scalable to every asthmatic in the world because it uses a digital infrastructure that’s already there. 

It’s a disruptive idea because it would require the pharmaceutical industry to shift its ‘asthma model’ from selling the maximum number of inhalers, to providing a subscription service that keeps people healthy, but actually sells fewer inhalers.

What is holding back disruptive innovation?  Most institutions are looking for reliable returns so do you think it’s down to the lack of capital available for riskier ventures?

We’re seeing flux in the political and environmental picture, and that kind of uncertainty naturally reduces the amount of risk that people and companies are willing to take.  On the other hand, this hesitation to innovate means more gaps are available for entrepreneurs and smaller businesses to explore.

We are also witnessing a major demographic shift, with Millennials and Gen Z coming of age with different values and assumptions. Many don’t know what life looked like without a smartphone, and they also put stronger emphasis on issues like the environment and equality than previous generations. They will be the decision makers in 5-10 years, and I think that will accelerate change.

Regulation will need to keep pace.  Governments and regulators will need to make much more use of digital technologies and even re-write the rules of competition. Relatively simple supplier and buyer relationships will turn into a much more complex ecosystem when businesses stop seeing their data as a nice add-on that helps them improve what they do, and start to use it to find new ways of doing things.